class: top, left, inverse, title-slide .title[ # Decomposing abundance change to recruitment and loss: analysis of the North-American avifauna ] .author[ ###
François Leroy
Marta Jarzyna
Petr Keil
] .institute[ ###
Czech University of Life Sciences,
Prague
Ohio State University ] --- # Temporal change of abundance * Sensitive indicator of biodiversity state * Perturbed by human activities * Average decline of relative abundance `\(\rightarrow\)` 69% (Living Planet Index) .center[ `\(\Rightarrow\)` -3 billion North-American birds since 70's ] .pull-left[ <img src="data:image/png;base64,#images/Rosenberg_Fig1.JPG" width="75%" /> ] .pull-right[ <br><br> <img src="data:image/png;base64,#images/Rosenberg_Fig2.png" width="150%" /> .footnote[ Rosenberg *et al.*, 2019 ] ] --- # Decomposing abundance change <br> .center[ <img src="data:image/png;base64,#images/deltaN_concept1.png" width="100%" /> ] -- <br> **Abundance change:** `$$\Delta N = N_{t1} - N_{t0} = R - L$$` <br> `$$\Leftrightarrow \Delta^2N = \Delta R - \Delta L$$` --- # Decomposing growth rate * **Growth rate:** per individual average change in population <br> `$$\frac{\Delta N}{N_{t0}} = \frac{R}{N_{t0}} - \frac{L}{N_{t0}}$$` <!-- `$$\Leftrightarrow \Delta Gr = \Delta (\frac{R}{N_{t0}}) - \Delta (\frac{L}{N_{t0}})$$` --> -- <br><br> .pull-left[ `$$\big\Downarrow$$` * **Recruitment rate** = individual addition of individuals `$$\frac{R}{N_{t0}}$$` ] .pull-right[ `$$\big\Downarrow$$` * **Loss rate** = individual probability of dying/emigrating `$$\frac{L}{N_{t0}}$$` ] --- class: inverse, center, middle ## Problem `\(\Rightarrow\)` Assessing the ongoing decrease of abundance does not tell us how loss and recruitment change through time -- `\(\Rightarrow\)` Decrease in recruitment `\(\neq\)` Increase in loss, but they both result in an acceleration of the decrease of abundance -- <br><br> ### From a conservation perspective `\(\rightarrow\)` measures to "bend the curve" of recruitment (*e.g.* working on reproductive sucess, protecting breeding habitat) `$$\neq$$` `\(\rightarrow\)` measures to "bend the curve" of loss (*e.g.* reduction of threats, increasing habitat quality) --- class: inverse, center, middle ## For North-American avifauna, we assessed: ### 1) temporal change of abundance, recruitment and loss from 1987 and 2021 -- ### 2) temporal change of growth rate, recruitment rate and loss rate -- ### 3) which process (recruitment or loss) is driving temporal change of biodiversity --- # Data - Breeding Bird Survey (BBS) .pull-left[ * Structured data on North American avifauna * From 1987 to 2021 ] .pull-right[ * More than 1000 routes * 564 species ] .center[ <img src="data:image/png;base64,#images/map_routes.jpg" width="70%" /> ] --- # Model - Dail & Madsen .pull-left[ * **Assess survival and recruitment from abundance data** ] .pull-right[ * Bayesian stacked hierarchical model ] `$$N_{t+1} = Survival_{t+1} + Recruitment_{t+1}$$` .center[ #### with ] `$$Survival_{t+1} \sim Bin(N_t, \omega)$$` `$$Recruitment_{t+1} \sim Poisson(\gamma)$$` `$$Loss_t = N_t - S_{t+1}$$` -- * Accounting for detection probabilities, depending on meteorological covariates: `$$N^*{_t} \sim Bin(N_t, p)$$` .center[ `\(\Rightarrow\)` **Sky condition, wind condition, temperature** & **time of the day** ] --- # Model - Dail & Madsen <!-- * 1 MCMC chain (= 1 core) with 100 000 iterations `\(\sim\)` **2 days** --> * 3 MCMC chains per species `\(\times\)` 564 species `\(=\)` **1692 MCMC chains** .center[ `\(\Rightarrow\)` **9.3 years** to fit the model using 1 core ( `\(\sim\)` 1 year using 8 cores) ] .pull-left[ .center[ **Marta Jarzyna** <img src="data:image/png;base64,#images/jarzyna.1.jpg" width="30%" /> ] ] .pull-right[ <br><br> * Ohio State University ] .center[ `\(\Rightarrow\)` Ohio SuperComputer to **parallelize** the learning on **1692 cores** <img src="data:image/png;base64,#images/OSC_logo.png" width="768" /> ] --- # Trend in abundance .center[ <img src="data:image/png;base64,#images/map_ab.jpg" width="100%" /> ] --- # Trend in recruitment .center[ <img src="data:image/png;base64,#images/map_rec.jpg" width="100%" /> ] --- # Trend in loss .center[ <img src="data:image/png;base64,#images/map_loss.jpg" width="100%" /> ] --- # Trends in abundance, recruitment and loss .center[ <img src="data:image/png;base64,#images/map_all_number.jpg" width="90%" /> ] --- # Trend in growth rate .center[ <img src="data:image/png;base64,#images/map_gr.png" width="100%" /> ] --- # Trend in recruitment rate .center[ <img src="data:image/png;base64,#images/map_recRate.png" width="90%" /> ] --- # Trend in loss rate .center[ <img src="data:image/png;base64,#images/map_lossRate.png" width="90%" /> ] --- # Trends in growth, recruitment and loss rates .center[ <img src="data:image/png;base64,#images/map_rates_all.png" width="90%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR1.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR2.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR3.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR4.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR5.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR6.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR7.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR8.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR9.png" width="75%" /> ] --- # Recruitment vs. Loss rates .center[ <img src="data:image/png;base64,#images/recRVsLossR100.png" width="75%" /> ] --- # Recruitment rate vs. Loss rate .center[ <img src="data:image/png;base64,#images/recRVsLossR.png" width="100%" /> ] --- <!-- # Recruitment rate vs. Loss rate in space --> <!-- .center[ --> <!-- ```{r, out.width="90%"} --> <!-- knitr::include_graphics("images/map_recRVsLossR.png") --> <!-- ``` --> <!-- ] --> <!-- --- --> # Recruitment rate vs. Loss rate (smoothened) .center[ <img src="data:image/png;base64,#images/map_recRVsLossR_gam.png" width="90%" /> ] --- # Species' preferred habitat - Numbers <br><br> .center[ <img src="data:image/png;base64,#images/barplots_number.png" width="100%" /> ] --- # Species' preferred habitat - Rates <br><br> .center[ <img src="data:image/png;base64,#images/barplots_rate.png" width="100%" /> ] --- # Conclusion .pull-left[ * At the **community level**: decrease in the number of extinction and recruitment drive biodiversity change <img src="data:image/png;base64,#images/recRVsLossR.png" width="95%" /> ] .pull-right[ * At the **individual level**: increase in recruitment and extinction rate are driving the population dynamic <img src="data:image/png;base64,#images/map_recRVsLossR_gam.png" width="95%" /> ] .pull-right[ ] --- # Conclusion `\(\Rightarrow\)` From a conservation perspective, working at the individual level is the most important <br> `\(\Rightarrow\)` Focus must be done on bending the loss rate curve (*e.g.* habitat loss, fragmentation, predation by domestic animals...) .center[ <img src="data:image/png;base64,#images/recRVsLossR.png" width="60%" /> ] --- class: inverse, center, middle # Ackowledgements .pull-left[ <svg viewBox="0 0 512 512" style="position:relative;display:inline-block;top:.1em;fill:white;height:1em;" xmlns="http://www.w3.org/2000/svg"> <path d="M464 64H48C21.49 64 0 85.49 0 112v288c0 26.51 21.49 48 48 48h416c26.51 0 48-21.49 48-48V112c0-26.51-21.49-48-48-48zm0 48v40.805c-22.422 18.259-58.168 46.651-134.587 106.49-16.841 13.247-50.201 45.072-73.413 44.701-23.208.375-56.579-31.459-73.413-44.701C106.18 199.465 70.425 171.067 48 152.805V112h416zM48 400V214.398c22.914 18.251 55.409 43.862 104.938 82.646 21.857 17.205 60.134 55.186 103.062 54.955 42.717.231 80.509-37.199 103.053-54.947 49.528-38.783 82.032-64.401 104.947-82.653V400H48z"></path></svg> leroy@fzp.czu.cz .center[ ### Marta Jarzyna <img src="data:image/png;base64,#images/jarzyna.1.jpg" width="30%" /> ] ] .pull-right[ <svg viewBox="0 0 512 512" style="position:relative;display:inline-block;top:.1em;fill:lightblue;height:2em;" xmlns="http://www.w3.org/2000/svg"> <path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"></path></svg> @FrsLry .center[ ### Petr Keil <img src="data:image/png;base64,#images/petr_keil.jpg" width="33%" /> ] ] .center[ <img src="data:image/png;base64,#images/ERC.JPG" width="2116" /> ] --- # Per species change - Abundance <img src="data:image/png;base64,#images/perSpecies_ab.png" width="2267" /> --- # Per species change - Recruitment <img src="data:image/png;base64,#images/perSpecies_rec.png" width="2268" /> --- # Per species change - Loss <img src="data:image/png;base64,#images/perSpecies_loss.png" width="2276" /> --- # Per species change - Growth rate <img src="data:image/png;base64,#images/perSpecies_gr.png" width="2268" /> --- # Per species change - Recruitment rate <img src="data:image/png;base64,#images/perSpecies_recR.png" width="2268" /> --- # Per species change - Loss rate <img src="data:image/png;base64,#images/perSpecies_lossR.png" width="2268" /> --- # Rec. vs. Loss colored by ab. trend <img src="data:image/png;base64,#images/rec_vs_loss_colored.png" width="2328" /> --- # Rec. rate vs. Loss rate colored by growth rate <img src="data:image/png;base64,#images/recR_vs_lossR_colored.png" width="2328" />